Mutation Churn Model
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RIS BIB ENDNOTEMutation Churn Model
Publication date: 24.03.2017
Schedae Informaticae, 2016, Volume 25, pp. 227-236
https://doi.org/10.4467/20838476SI.16.017.6198Authors
Mutation Churn Model
Mutation testing is considered as one of the most effective quality improvement technique by assessing the strength of the actual test suite. If no test is able to kill a given mutant, this means that the tests are not strong enough and we need to write additional one that will be able to kill this mutant. However, mutation testing is very time consuming. In this paper we investigate if it is possible to reduce the scope of the mutation analysis by running it only on the new or changed part of the code. Using data from the real open-source projects we analyze if there is a relation between mutation scope reduction and effectiveness of the mutation analysis.
[1] Millo R.A.D., Lipton R.J., Sayward F.G., Hints on test data selection: help for the practicing programmer. IEEE Computer, 1978, 11(4), pp. 34–41.
[2] Ammann P., Offutt J., Introduction to Software Testing. Cambridge University Press, Cambridge, UK, 2008.
[3] Zhang L., Marinov D., Khurshid S., Faster mutation testing inspired by test prioritization and reduction. In: ISSTA 2013 – Proceedings of the International Symposium on Software Testing and Analysis, 2013, pp. 235–245.
[4] Usaola M.P., Mateo P.R., Mutation testing cost reduction techniques: A survey. IEEE Software(, 2010, 27, pp. 80–86.
[5] Kim S., Clark J.A., McDermid J.A., Investigating the effectiveness of objectoriented testing strategies using the mutation method, software testing. Verification and Reliability, 2001, 11 (3), pp. 207–225.
[6] s. Ma Y., r. Kwon Y., Offutt J., Inter-class mutation operators for java. In: Proceedings of the 13th International Symposium on Software Reliability Engineering, IEEE, 2002, pp. 352–363.
[7] Papadakis M., Traon Y.L., Metallaxis-fl: mutation-based fault localization. Software Testing, Verification and Reliability, 2015 (25), pp. 605–628.
[8] PIT Mutation Testing. http://pitest.org/, Accessed: 2016-12-30.
Information: Schedae Informaticae, 2016, Volume 25, pp. 227-236
Article type: Original scientific article
Faculty of Mathematics and Computer Science, Jagiellonian University, Krakow, Poland
Faculty of Mathematics and Computer Science, Jagiellonian University, Krakow, Poland
Faculty of Mathematics and Computer Science, Jagiellonian University, Krakow, Poland
Published at: 24.03.2017
Article status: Open
Licence: None
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